European Journal of Public Health, Vol. 15, No. 2, 133–139
q The Author 2005. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
doi:10.1093/eurpub/cki125 Advance Access published on 8 March 2005
...........................................................................................
Bridging the gap between doctors
and policymakers
The use of scientific knowledge in local school health care
policy in The Netherlands
Wim H.M. Gorissen1, Tom W.J. Schulpen2, Antoon H.M. Kerkhoff3,
Oscar van Heffen3
Background: The decentralization of school health care policy in The Netherlands was followed by an
increase in diversity, which was most often not evidence-based. This study aims to clarify the use of
scientific knowledge in school health care policy-making processes: multi-actor processes in networks,
trying to solve certain problems. Methods: Case-study design in four Municipal Health Service regions,
using documents and half-structured interviews as data sources. Results: Scientific knowledge is used
by only 42% of the actors in 58% of decision-making rounds in policy-making processes. ‘Recent’
regional data on health indicators are used more often than ‘established’ (inter)national knowledge
of theoretical models. Mainly school health professionals use knowledge as a resource to influence the
policy process. Other actors (e.g. managers and municipalities) use formal power, money or ‘initiative’
as their main resources. Powerful actors put forward less scientific knowledge than actors in
dependent positions. Individual actors with a combined scientific and political frame of reference put
forward knowledge most frequently, especially in complex networks with many actors, more than one
powerful actor, more than one arena, more than one dominant resource and more than one
dominant frame of reference. Conclusion: The use of scientific knowledge in school health care policymaking processes can and must be improved. Liaison officers can bridge the gap between doctors and
policymakers, especially in complex policy networks. They combine a scientific and a political frame of
reference and act upon scientific knowledge as a resource in their efforts to influence the policymaking process.
Keywords: policy networks, resource dependence approach, school health care, use of knowledge
...........................................................................................
Health Care (SHC) in The Netherlands is carried out
School
by Municipal Health Services (MHSs) and is subject to
municipal politics.1 Since the beginning of the 20th century, a
growing number of school doctors has been employed by
municipalities.2 After the Second World War, state subsidies
promoted the development of national school health services
and more or less imposed standardization of activities, with
periodic school health examinations as their main activity. The
Collective Prevention Act (1990) gave more freedom to
municipalities to adapt SHC to their needs. This resulted in
divergent policies in SHC practice between MHS regions. One
MHS completely abandoned the periodic school health
examinations, replacing them with school-oriented health
education activities, while another still examined all children
four times during their school career.
This increasing diversity was considered undesirable in view
of the development of evidence-based SHC, in which regional
aims and targets as well as intervention instruments should be
based on the best available scientific knowledge.3 – 5 Instead of
.......................................................
1 Municipal Health Service Utrecht, Department of Child and
Adolescent Health, Utrecht, The Netherlands
2 University Medical Centre, Department of Social Paediatrics, Utrecht,
The Netherlands
3 University of Twente, Faculty of Public Administration and Public
Policy, Enschede, The Netherlands
Correspondence: Wim H.M. Gorissen MD, PhD, Koeweitdreef 14, 3564
HC Utrecht, The Netherlands, tel. +31 20 5198799, fax +31 20 5198800,
e-mail: [email protected]
scientific knowledge, a diversity of local interests appeared to
determine the policy-making processes. SHC professionals
appeared to have a poor understanding of how municipal
policies are made. Therefore they seemed unable to play a part
as actors in these policy-making processes and were not able to
help policy makers to find a balance and cooperation between
local interests and scientific knowledge.
This study aims to clarify the limited use of scientific
knowledge in SHC policy-making processes and the poorly
understood relationship between research and policy.6
Theoretical framework
A policy-making process can be seen as problem solving. In
general it is a process consisting of rounds in which divergent
actors are involved with mutual power-dependency relations,
usually having different frames of reference and using different
resources. It is characterized by a sequence of actions with a
recognizable course. It is more a social (political) process, than a
rational analytical process.7,8
Policy-making processes are realized in networks of actors.
Actors are individuals (e.g. a school nurse), groups of
individuals (e.g. a group of school doctors) or organizations
(e.g. a MHS), who interact with each other,7 while trying to
influence the outcome of the policy-making process.
The social systems in which actors interact are called policy
networks.9 – 11 Within these policy networks, sub-networks or
‘arenas’ are recognised.12,13 Policy-making processes can be
segmented into decision-making rounds: the period between
two crucial decisions.12,14,15
134
European Journal of Public Health Vol. 15, No. 2, 133–139
In their efforts to influence the outcome of the policy-making
process, actors use resources such as formal authority, money,
workforce, expertise/knowledge and access to information (see
table 2).16 – 18 Power-dependency relations between actors are
based on the control of one actor over resources on which other
actors depend.18 – 20
Frames of reference are the ‘spectacles’ through which actors
look at the world. For the purpose of this study, they are defined
as scientific, economic, juridical and political.21,22 The scientific
frame considers scientifically established knowledge as crucial to
the rational solution of policy problems. The political frame of
reference emphasizes that the solution of problems is a matter of
yielding power. The juridical frame focuses on the necessity that
policies safeguard the ‘trust in justice’ and the enforcement of
juridical rules. The economical frame stresses that policies
primarily distribute the limited amount of resources on which a
community relies.
The definition of ‘scientific knowledge’ is much debated. In
the public health sector, empirical knowledge and ‘evidencebased healthcare’ are considered to be of particular importance.5
Therefore (scientific) knowledge is, for the purpose of this
study, defined as: insights from research that, by means of
collection and analysis of data, contribute to the understanding
of (i) the health of children, (ii) its determinants and (iii)
instruments to improve it.23 It is distinguished into three
interrelated antonyms (see table 1):
† (epidemiological) fact knowledge versus empirically
grounded theoretical-model knowledge on causalities;
† ‘established’ knowledge from the ‘body of knowledge’ of a
field of science versus ‘recent’, possibly not yet generally
accepted, knowledge;
† regionally bound knowledge versus knowledge from the
(inter)national literature.
These antonyms can, on a municipal level, be clustered as recent
regional epidemiological fact knowledge versus established
theoretical-model knowledge from the (inter)national
literature.
The communication between the fields of research and policy
is problematic. It is nevertheless of crucial importance to an
evidence-based SHC.24 – 27
In this study we explore the relation between these variables.
Our hypothesis is that the use of scientific knowledge in policymaking processes can be explained by the characteristics of
actors and the networks in which they interact.
Table 1 Use of knowledge by actors (first column) and in
decision-making rounds (second column; one or more
indications of use of knowledge in an interview or a
document)
Aspects of use of knowledge
Actors
(n 5 133)
Rounds
(n 5 52)
No.
No.
%
%
Type of knowledge
.................................................. .
(Epidemiological) fact knowledge
41
31%
28
49%
Knowledge of theoretical models
35
26%
21
37%
.................................................. .
.................................................. .
Degree of acceptance of knowledge
.................................................. .
Established knowledge
40
30%
16
28%
Recent knowledge
44
33%
29
51%
.................................................. .
.................................................. .
Territoriality of the knowledge
.................................................. .
Regionally bound knowledge
37
28%
28
49%
(Inter)national knowledge
35
29%
22
39%
56
42%
33
58%
.................................................. .
.................................................. .
Total use of knowledge
Table 2 Prevalence of actor-characteristics in actors (first
column) and the relation of the actor-characteristics with the
use of knowledge (second column; chi-square tests, Fisher’s
exact tests for small numbers, or analysis of variance for
continuous dependent variable; n ¼ 133)
Resources
Prevalence
in actors (%)
Relation to use
of knowledge
Formal authority
54
++
Money
35
n.s.
Workforce
84
+
Other physical resources
25
++
Appeal to legislation
13
++
Access to target population
15
n.s.
Relations
41
n.s.
Experience
22
n.s.
Expertise
71
++
Personal skills
27
+++
Access to information
53
+++
Reputation
20
+++
Power rate
(continuous)
2
.................................................. .
.................................................. .
.................................................. .
.................................................. .
.................................................. .
.................................................. .
.................................................. .
.................................................. .
Study design
The central research question of the study is therefore
formulated as follows: Are the characteristics of actors, and
networks in which they operate, related to scientific knowledge
being put forward in policy-making processes in SHC in The
Netherlands?
This central question is elaborated into three sub-questions,
referring to:
† The type of knowledge used.
† The relation with the characteristics of the actors in a
network.
† The relation with the characteristics of the networks in a
decision-making round.
The case-study method is used to study these questions.28 – 30 The
research domain is limited to the SHC for 4–19-year-olds31,32 in
the last decade of the 20th century.1 The cases (policy-making
processes) are selected as the ‘most different’ policy subjects and
MHS regions. The study is confined to five policy subjects:
.................................................. .
.................................................. .
.................................................. .
.................................................. .
.................................................. .
Frames of reference:
.................................................. .
(Medical) scientific
53
+++
Economic
31
+
.................................................. .
.................................................. .
Juridical
5
n.s.
Political
50
+
Combined scientific
and political
38
+++
.................................................. .
.................................................. .
+, ++, +++: P ,0.10, P , 0.05, P , 0.01, respectively, all with a
positive association.
2 , P , 0.05, with a negative association.
n.s., not significant.
The gap between doctors and policymakers
1. General SHC policy: the main choices between an individual
or a group approach; orientation on all children or a riskoriented approach and focus on somatic or psychosocial
problems.
2. Health-promoting schools: a systematic approach of health
promoting activities in schools.
3. Pedagogical support to parents: courses for parents with
minor educational problems.
4. Community networks youthcare: participation in neighbourhood-based networks of various professionals working with
multi-problem families.
5. Bed-wetting counselling: ambulatory dry-bed training.
Policy-making processes have been studied in two urban
(Utrecht, The Hague) and two rural MHS regions (Groningen,
North-Limburg) with different general SHC policies.
In total we reconstructed 20 policy-making processes in these
four regions and on the five policy subjects mentioned. In doing so,
we collected 166 text sources from MHS archives (policy papers,
meeting minutes, correspondence etc.) and conducted 77 semistructured interviews with regional actors. Most text sources and
interviews referred to more than one policy-making process.
The computer program Kwalitan, version 4.0, was use to
support qualitative analyses.33 The computer program SPSS,
version 10.0, was used to perform quantitative analyses.34
Operationalization
The use of knowledge is made operational into indicators for
the use of knowledge at the actor-level (which of the three
antonyms of knowledge previously defined does an actor use),
and indicators for the use of knowledge at the network level
(which of the antonyms are used in a decision-making round).
The analysis at the network level can be considered as an
‘ecological’ analysis.35
All theoretical concepts are made operational into indicators
at these two levels of analysis: actor characteristics and network
characteristics.
Three categories of actors are distinguished: (i) SHC internal
actors (e.g. SHC managers and school doctors), (ii) other MHS
internal actors (e.g. director of MHS and health promotion
professionals) and (iii) MHS external actors [e.g. municipalities
(a collective noun for mayor, aldermen and city council),
municipal officials, schools and regional mental health services].
Further actor characteristics are:
† the use of resources,
† power rates (the perceived relative power of an actor),
† frames of reference.
In the four MHS regions 133 actors were identified. The
values of the characteristics of these actors are measured by
‘counting’ the number of text sources and interviews in which
‘clues’ are found, for example the use of a resource or the
existence of a power– dependency relation between two actors.
A ‘clue’ is a text fragment or a statement derived from an
interview, from which it can be concluded that, for example, the
actor ‘SHC manager’ did use the resource ‘formal authority’ to
force school doctors to follow a guideline (resource use by
actor), or that a school nurse asked approval of the school
doctor to start an ambulatory dry-bed training (power–
dependency relation between two actors). Two researchers
coded the clues independently; differences in coding were
resolved in discussion.
The network characteristics are:
† prominence of actors in the network and their grouping in
arenas (SHC internal, MHS internal and MHS external),
135
† dominant resources (used by most prominent actors) in the
network,
† type and number of powerful actors (with high power rates),
† dominant frames of reference (present in most prominent
actors) in the network.
In the 20 SHC policy-making processes, 52 decision-making
rounds were recognised (from one up to five rounds in one
process). The values to the network characteristics of these
rounds are judged using a qualitative analysis of the reconstructions of the policy-making processes in combination with the
results of the analysis of the actor characteristics (‘ecological’
analysis). This combination was necessary, because many of the
text sources and interviews did not refer to only one round of
one policy-making process.
For example, school doctors were prominent and powerful
actors in the total policy-making process on bed-wetting
counselling. In the first round the school doctors prevented
the school nurses from starting dry-bed training. In the second
round, however, the school nurses negotiated the start of a
project with the new SHC manager, without having to
deliberate with the school doctors, who protested in vain. So
in the first round the school doctors are coded as prominent and
powerful, but in the second round only as prominent actors.
Power positions apparently changed between the first and
second round.
Two data-matrices are set up: one with the actor characteristics of and the use of knowledge by the 133 actors and a second
with the network characteristics of and the use of knowledge in
the 52 decision-making rounds. The associations between the
variables in each data-matrix are analysed using chi-square (x2)
tests, Fisher’s exact tests and linear and logistic regression
analyses.
Results
Use of knowledge
At least one indication of any type of knowledge being put
forward is found in 42% of the actors (predominantly SHC
internal actors and health promotion professionals; mean
number of indications in ‘users’ of knowledge: 3.89) and in
58% of the decision-making rounds in policy-making processes
(see table 1). ‘Recent’ knowledge (51%), (epidemiological) fact
knowledge (49%) and regionally bound knowledge (49%) are
used in more rounds than ‘established’ knowledge (28%),
theoretical-models knowledge (37%) or (inter)national knowledge (39%). To illustrate this tendency to use recent regional
epidemiological fact knowledge in preference to established
international theoretical-models knowledge, we cite a municipal
working party on health policy, chaired by an MHS employee,
which used recent epidemiological data, collected by the same
MHS, for prioritizing health fields.
Actor characteristics
Actors predominantly use the resources: workforce, expertise,
formal authority and access to information (see table 2, first
column). SHC internal actors use a wider range of different
resources than other actors: formal authority, workforce,
experience, expertise, access to information and reputation.
Other MHS internal actors use mainly formal authority,
personal skills (e.g. psychological skills or eloquence) and access
to information. MHS external actors use relatively often the
resources of money and access to target population (e.g.
children in schools).
MHS directors and SHC managers are powerful within their
organization or department, but are dependent when they go
outside. SHC internal actors are less powerful than other MHS
internal actors and some MHS external actors: political actors
136
European Journal of Public Health Vol. 15, No. 2, 133–139
and municipal officials. There is a relation between the use of
resources and the power rate. Actors who are considered
powerful use the resources of formal authority and money more
often. Actors who are considered dependent, mainly use the
resources of workforce, expertise, access to information and
‘other physical resources’ (e.g. the availability of a building in
which they work).
The scientific and political frames of reference are more
widespread than the economic one. A juridical frame of
reference is practically absent. In SHC internal actors, a
scientific frame of reference is found relatively often (83%), as
well as a combination of frames of reference (55%). Other
MHS internal actors (e.g. MHS directors) have a political
frame of reference relatively often. Actors with more frames of
reference use more different resources (linear regression,
P , 0.01).
Use of knowledge related to actor characteristics
Knowledge is put forward more often by actors who use the
resources: formal authority (50% versus 33%: x2 test: P , 0.05),
access to information (56% versus 26%: P , 0.01) and expertise
(48% versus 28%; P , 0.05; see also table 2, last column).
Actors who use more different resources also use more
knowledge (ANOVA: P , 0.01). The other significant relations
are less relevant because of the lower prevalence of the resources
(, 33%). Due to the method used to judge the value of the
indicators (one or more clues in text sources or interviews), the
analysis is liable to overestimate relations.
Powerful actors use less knowledge than dependent actors
(linear regression; P , 0.05).
The combination of a scientific and a political frame of
reference in one single actor is related to a much higher level of
use of knowledge (76%) than the presence of either one (38%
and 31%) or none of these frames (18%; x2 test: P , 0.01: see
figure 1). Actors with these two frames of reference are therefore
referred to as ‘liaison officers’.
Network characteristics in decision-making rounds
As expected, SHC internal actors are prominent actors in most
rounds: SHC managers (in 86% of the 52 rounds), school
doctors (77%) and school nurses (72%). Health promotion
professionals (49%) and MHS directors (42%) are also
prominent in many rounds. Most rounds consist of one
arena, 39% have two arenas.
The resources: workforce, formal authority and expertise, are
dominant in most decision-making rounds (see table 3, first
column).
SHC managers (44%) and MHS directors (37%) are
considered powerful in comparatively many rounds. Municipalities (25%), school doctors (19%) and health promotion
professionals (16%) are considered powerful in fewer rounds.
Municipalities are often powerful in one round in a policymaking process that consists of more rounds. SHC managers
and MHS directors, on the other hand, are usually powerful in
more rounds in one process. When municipalities are
prominent actors, they are almost always powerful (in 14 out
of 15 rounds in which they are prominent actors). This is in
contrast to school nurses, who are often prominent, but almost
never powerful actors (only in 3 out of 41 rounds in which they
are prominent actors).
In almost all decision-making rounds the scientific frame of
reference is dominant. The political and economical frames are
dominant in fewer rounds, and usually in combination with a
scientific frame.
Networks can be divided into simple and complex networks.
Simple networks are characterized by few dominant resources
and frames of reference, with one arena and one powerful actor.
Complex networks have opposite characteristics: more dominant resources and frames of reference, two arenas and more
than one powerful actor.
Use of knowledge related to network characteristics
The presence in the network of MHS directors or health
promotion professionals, is related to more use of knowledge by
(other) actors in the network (x2 test; P , 0.05). The presence
of more than one arena (usually an SHC internal arena and an
SHC external arena) is also related to more use of knowledge
(P , 0.05; see table 3, last column). The presence of more
dominant resources is related to more use of knowledge (linear
regression; P , 0.05).
In rounds in which SHC managers (x2 test; P , 0.01) or
MHS directors (P , 0.05) are powerful, other actors often use
knowledge. The presence in the network of more than one
powerful actor is related to more use of knowledge (linear
regression; P , 0.01).
The dominant presence of a scientific as well as a political
frame in one decision-making round is related to more use of all
aspects of knowledge (67% versus 50% for total use of
knowledge; not significant).
Figure 1 Combined frames of reference and use of knowledge by actors
The gap between doctors and policymakers
Table 3 Prevalence of network-characteristics in decisionmaking rounds (first column) and the relations of the networkcharacteristics with the use of knowledge (second column; chisquare tests, Fisher’s exact tests for small numbers, or analysis
of variance for continuous dependent variable; n ¼ 52)
More than one arena
Prevalence
in rounds (%)
Relation to use
of knowledge
39
++
.................................................. .
137
frame of reference and use a wider range of different
resources.
† Complexity of a policy network (more dominant resources,
more frames of reference, more arenas and more powerful
actors) is related to more use of knowledge.
Discussion
Dominant resources:
.................................................. .
Formal authority
81
n.s.
Money
32
n.s.
Workforce
88
n.s.
Other physical resources
0
n.s.
Appeal to legislation
0
n.s.
Access to target
population
7
n.s.
.................................................. .
.................................................. .
.................................................. .
.................................................. .
.................................................. .
.................................................. .
Relations
11
n.s.
5
n.s.
74
n.s.
7
n.s.
28
++
2
n.s.
Three ore more
dominant resources
71
++
More than one
powerful actor
60
.................................................. .
Experience
.................................................. .
Expertise
.................................................. .
Personal skills
.................................................. .
Access to information
.................................................. .
Reputation
.................................................. .
.................................................. .
2
.................................................. .
Dominant frames of reference
.................................................. .
(Medical) scientific
96
n.s.
Economic
37
n.s.
Juridical
0
n.s.
Political
51
n.s.
More than one frame
of reference
62
n.s.
Complexity of
the network
(continuous)
.................................................. .
.................................................. .
.................................................. .
.................................................. .
.................................................. .
++
++, P ,0.05, with a positive association.
2 , P , 0.05, with a negative association.
n.s., not significant.
Generally speaking, a greater complexity of the network is
related to more use of knowledge (linear regression;
P , 0.05).
This leads to the following answers to the research questions:
† In 42% of the actors and in 58% of the decision-making
rounds in SHC policy-making processes, at least one
indication is found for the use of scientific knowledge.
Recent regional epidemiological fact knowledge is used more
often than established (inter)national theoretical-models
knowledge.
† MHS directors, SHC managers and other SHC internal
actors use knowledge relatively often. MHS directors and
SHC managers do so mainly in (for them) external arenas,
where they are less powerful. The use of knowledge is
minimal in powerful actors and extensive in liaison officers.
These are the actors who combine a scientific and political
Use of knowledge
The use of scientific knowledge in SHC policy-making processes
is open to improvement. In a considerable number of the
decision-making rounds (42%), no evidence was found for any
use of scientific knowledge. Many actors (58%), even SHC
internal actors, did not put forward scientific knowledge at all.
Three possible causes for this finding are discussed: insufficient
availability, insufficient accessibility or insufficient readiness to
the use of knowledge.
Availability and accessibility of knowledge
Insufficient availability of scientific knowledge is at least of some
importance. A recent Dutch study on the availability of
knowledge of the effects of SHC activities, supports this
assumption.36 The effectiveness of many SHC activities has
never been studied properly; (systematic) reviews are scarce. To
resolve this problem, co-operation between universities,
national research institutes and regional MHSs is needed.
Insufficient accessibility to knowledge may partially explain
the lagging behind of the use of established (inter)national
knowledge of theoretical models, compared to the use of recent
regional epidemiological facts, which are often produced by
employees of the same MHSs in which they are also actors in the
policy-making processes. This problem can partly be solved
using modern information technology, e.g. by means of access
to the internet.
It has to be mentioned that the finding that established
international theoretical-models knowledge is used less, can be
explained in part by professionals assuming they share this
knowledge and therefore seeing no need in putting that forward.
This assumption is consistent with the finding that SHC internal
actors use less knowledge in SHC internal networks than in SHC
external networks.
Readiness to use knowledge
The presence of a combined scientific and political frame of
reference, as well as the existence of complex networks, appears
to increase the readiness to put forward scientific knowledge.
This can be illustrated by the following. In a transition from an
SHC internal to an SHC external arena, the SHC internal actors
are confronted with relatively powerful actors. This ‘confrontation’ leads to a need to use a wider range of different resources
for the SHC internal actors and probably therefore to more use
of knowledge. Relatively powerful actors (like the SHC manager
in an exclusively SHC internal arena) have little need to use
other resources or scientific knowledge, besides the resources of
money and formal authority. The use of knowledge seems to
have to ‘compete’ with the mentioned resources, which are ‘easy
accessible’ resources for powerful actors: using power is easier
than arguing it out. When more powerful actors are present,
they can rely less on their formal authority and money, but need
to substantiate points of view with knowledge. An example is a
SHC manager (power rate 0.60), who uses his own survey data
to emphasize the importance of periodic health examinations
when confronted with a critical city council (power rate 0.79).
The presence of more then one powerful actor also encourages
other actors to throw in their knowledge, because thus they are
more likely to convince at least one powerful actor of their point
138
European Journal of Public Health Vol. 15, No. 2, 133–139
Figure 2 The use of knowledge in policy-making networks
of view. The conclusion is that complexity of the network, in
general, encourages the use of knowledge.
It appears that, particularly, actors who are able to link the
scientific and political approaches, use knowledge in the
complex networks mentioned. They are referred to as liaison
officers: persons who are familiar with the nature of the
research process, the professional process and the policymaking process and are therefore able to ‘translate’ questions
and answers to and fro. They are the actors with a combined
scientific and political frame of reference illustrated in figure
1. Better than other actors, they are able to realize the
importance of bringing up the right knowledge at the right
time in the right policy-making processes. Actors with a
scientific frame of reference prefer the use of international
theoretical-models knowledge; actors with a political frame of
reference prefer the use of regional epidemiological fact
knowledge. Even on this level the liaison officers appear to
close a gap: we found that they use both types of knowledge
more often. They seem more aware of the importance of
combining both types of scientific knowledge to establish
rational policies. They are also more likely to be able to put
forward scientific knowledge adequately, because they have a
better understanding of the policy-making process and the
demands it imposes on actors who want to exert influence.
Departments of SHC would do well, therefore, to see to it
that they have liaison officers at their disposal. These liaison
officers can regulate the communication and bridge the gap
between professionals, managers, researchers and municipalities. Health promotion professionals and epidemiologists
should likewise improve their liaison skills.
Other authors also concluded that the availability and
accessibility of knowledge only, does not guarantee its use.
Weiss describes frames of reference as ‘filters’, through which
new information has to pass before it is admitted to a policymaker’s ‘stock of knowledge’. Some of these filters are: the
relevance of the knowledge to their work, the quality of the
research, the plausibility of the results and the explicitness and
feasibility of the recommendations. She also points out that
knowledge is often not used by actors at the very moment it
is presented to them. Not until a policy-maker encounters a
problem does he consult his ‘stock of knowledge’.24,37
Nutbeam argues that research is more likely to influence
policy when it takes into account the experience of
practitioners in delivering programmes, and of the public
who are intended to benefit from the different types of public
health interventions.38 Elliot points to the informal use of
knowledge and the importance of long-term relations between
policy-makers and ‘trusted researchers’. To reach the status of
trusted researcher, the researchers must have gained respect
and trust; among other things by showing they understand
how (in this case) the British National Health Service works.
She argues in favour of a ‘dialogical’ model of the use of
knowledge, instead of the more popular ‘problem-solving’
model, which, in her opinion ‘only exists in the mind of
researchers’.39 Lomas and others also point to the differences
in frame of reference between researchers and policy makers,
and to the importance of responsive researchers and of
‘receptors for research’ in health departments, in creating
points of exchange between these two worlds.40 – 43
Conclusion
The interaction between an SHC internal and an SHC
external arena with (other) powerful actors appears to call for
knowledge to support points of view. This ‘confrontation’ is
stronger when, apart from the distribution of power, different
resources are also used and different frames of reference are
present. Therefore, in complex networks the use of knowledge
is encouraged.
The presence of liaison officers, who combine a scientific and
a political frame of reference and therefore can act as a point of
exchange between these worlds, appears to be a requirement for
the effective and beneficial use of knowledge in policy-making
processes. The need for liaison officers is even greater in
complex networks. They must be found within the regular
workforce of the public health sector. Policy-makers should
actively become ‘receptors of research’ or employ such persons.
This implies that school health professionals (e.g. school
doctors, epidemiologists, health promotion professionals) and
their managers need to acquire more understanding of the
nature of the policy-making process in order to be able to play
an effective liaison role in these processes. Only then can the gap
between doctors, managers, researchers and (other) policymakers be bridged and a more evidence-based SHC be achieved.
Key points
† This study aims to clarify the use of scientific
knowledge in school health care policy-making
processes.
† Scientific knowledge is used by only 42% of the actors
in 58% of decision-making rounds in policy-making
processes.
† ‘Liaison officers’ combine a scientific and political
frame of reference and use scientific knowledge to
influence the policy-making process.
† Liaison officers can bridge the gap between doctors and
policy-making, especially in complex policy networks.
The gap between doctors and policymakers
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